scholarly journals Comparison of Dynamic Voltage Scaling (DVS) of Core Voltage Using the On-board Voltage Regulator and External Voltage Regulator via I2C Protocol in Automotive Micro controller

2021 ◽  
Vol 23 (06) ◽  
pp. 794-804
Author(s):  
Kiran Guruprasad Shetty P S ◽  
◽  
Dr. Ravish Aradhya H V ◽  
Eswar Goda ◽  
◽  
...  

Dynamic Voltage Scaling is performed on automotive micro-controller AURIX from Infineon Technologies. In this micro-controller the core and different IPs operate on the 1.25 V supply rail, so dynamically voltage is changed according to the workload in the micro-controller. DVS is done either using an internal onboard voltage regulator or an external voltage regulator. An External board (KITPF3000FRDMEV), which has a controller and a Power Management Integrated Circuit (PMIC) is used for changing the supply voltage to the micro-controller during DVS using an external voltage regulator. The micro-controller is predicting the workload and according to workload, the control command is sent to the controller (FRDM-KL25) in the kit through I2C communication and then the controller sends the command to adjust the voltage of PMIC (PF3000) through I2C communication. Both current measurements for the internal voltage regulator and external voltage regulator are measured for various loads and latency is measured for various baud rates while using external voltage regulator through I2C protocol.

Author(s):  
Arya Lekshmi Mohan ◽  
Anju S. Pillai

Dynamic Voltage Scaling is an innovative technique for reducing the power consumption of a processor by utilizing its hardware functionality. Dynamic Voltage Scaling processors are mainly focusing on power management. Such processors can be switch between discrete frequency and voltage levels. The main challenges of Dynamic Voltage Scaling are increased number of preemptions and frequency switching. A part of dynamic energy as well as CPU time is lost due to these processes. To limit such processes, an algorithm is proposed which reduces both unwanted frequency switching and preemptions.


2012 ◽  
Vol 47 (11) ◽  
pp. 2563-2575 ◽  
Author(s):  
Yu-Huei Lee ◽  
Chao-Chang Chiu ◽  
Shen-Yu Peng ◽  
Ke-Horng Chen ◽  
Ying-Hsi Lin ◽  
...  

2008 ◽  
Vol 17 (06) ◽  
pp. 1111-1128 ◽  
Author(s):  
DAVID WOLPERT ◽  
PAUL AMPADU

Temperature and voltage fluctuations affect delay sensitivity differently, as supply voltage is reduced. These differences make runtime variations particularly difficult to manage in dynamic voltage scaling systems, which adjust supply voltage in accordance with the required operating frequency. To include process variation in current table-lookup methods, a worst-case process is typically assumed. We propose a new method that takes process variation into account and reduces the excessive runtime variation guardbands. Our approach uses a ring oscillator to generate baseline frequencies, and employs a guardband lookup table to offset this baseline. The new method ensures robust operation and reduces power consumption by up to 20% compared with a method that assumes worst-case process variation in filling a lookup table.


2014 ◽  
Vol 631-632 ◽  
pp. 373-377 ◽  
Author(s):  
Yan Kang ◽  
Zhong Min Wang ◽  
Ying Lin ◽  
Yi Fan Zhang

Energy consumption can be optimized by utilizing dynamic voltage scaling that conjointly adjusts the supply voltage and the operational frequency during the execution of the tasks to effectively minimize the energy. An improved estimation of distribution algorithm is presented for energy saving of the distributed embedded systems that consists of dynamic voltage scalable processing elements. The algorithm evolves computation by using the univariate marginal distribution to search the solution in a discrete space and mapping the solutions into feasible ones stratified the precedence constraint. The algorithm hybridize the genetic algorithm with estimation of distribution algorithm by combines statistically learning and sampling the probability distribution of the population iteratively and the conventional evolutionary operators such as crossover and mutation together. Simulated annealing is utilized to accept some bad solution rather the elite solution to make fully use of the global and local information. Experiments are implemented to demonstrate the performance of the algorithm


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